1. USE OF INTENT INFORMATION IN AIRCRAFT CONFORMANCE MONITORING
Tom G. Reynolds & R. John Hansman
&
MIT International Center for Air Transportation

2. RESEARCH APPROACH
Main objectives of ATC: keep aircraft separated without unduly impeding traffic flows
Knowledge of future behavior (intent) is fundamental to:
Enable controller to establish a ‘plan’ to achieve these objectives
Determine whether this plan is being followed or not
Define a state vector X(t) containing:
Current dynamic states
Position
Velocity
Acceleration
Higher order states representing future behavior
INTENT

3. ‘TRUE’ & ‘SURVEILLANCE’ STATE VECTORS
XT(t) = ‘True’ state vector containing the actual aircraft states
XS(t) = ‘Surveillance’ state vector used by controller containing measured or inferred aircraft states
Only a subset of states may be directly surveilled in XS(t): controller infers others or controls without regard of those components

4. PILOT / AIRCRAFT INTERACTION
PILOT i
Pilot’s
INTENT
IPi(t) i
FMS or MCP
inputs
Aircraft i
trajectory
CONTROL
LAW
Autopilot
Aircraft
INTENT
IAi(t) ∫ ∫
A/c
target
states
Control
surface
inputs
Ai(t)
Vi(t)
Ri(t) -
Lag
AIRCRAFT i
Actual dynamic states

5. MOTIVATION FOR INTENT
Need for ‘surveilled intent’ representing the controller’s inference of the future behavior of aircraft in state space
Inferring intent is logical extension to inferring lower order states (position, velocity, etc.)
Intent not well defined in literature: need to tailor to this situation
Approach taken defines intent based on formalism used in the operational ATC environment:
Flight Plan
Clearances & vectors
Autopilot & FMS programming

6. ATM BASIC CONTROL LOOPS WITH INTENT FLOW
Surveillance
En route: 12.0 s
Terminal: 4.8 s
PRM: 2.4 s
ADS: 1.0 s
HOST
Flight Plan
Flight Strip
Decision
Aids
. .
ATC
Displays
Flight Plan
Amendments
Vectors
Voice
AOC
Airline
Ops
Center
Voice
PILOT
ACARS (Datalink)
CDU
MCP
CONTROLS
Displays
Trajectory
commands
State
commands
Manual
control
Initial
clearances
Autopilot
Autothrust
AIRCRAFT
FMC
State
Navigation

7. DEFINING INTENT Working definition of intent:
Future actions of aircraft which can be formally articulated & measured in the current ATC/flight automation system communication structure
Aircraft is controlled to a set of ‘Current target states’ (e.g. airspeed, altitude, heading)
Current target states are driven from the ‘4D planned trajectory’
Planned trajectory driven by ‘Destination’

8. INTENT CONSISTENCY BETWEEN ATC AGENTS
Define:
IGi(t) = intent for aircraft i as programmed into the ground automation system (e.g. HOST Computer System)
ICi(t) = controller’s intent for aircraft i
IPi(t) = pilot i’s intent for his/her aircraft
IAi(t) = intent for aircraft i as programmed into the autoflight system
IGi(t) = ICi(t) = IPi(t) = IAi(t) for consistent intents for aircraft i
Inconsistencies in intent between system agents (e.g. controller, pilot & aircraft/ground automation) may lead to the development of a hazardous situation

9. EXAMPLES OF INTENT INCONSISTENCY BETWEEN ATC AGENTS
Pilot misunderstands clearance, IG(t) = IC(t)  IP(t) = IA(t)
Autoflight system omission/programming error, IG(t) = IC(t) = IP(t)  IA(t)
Host Computer System not updated, IG(t)  IC(t) = IP(t) = IA(t)
Controller, C
Ground automation
(HOST), G
IG(t)
IC(t)
Future
trajectory
IP(t)
IA(t)
Pilot, P
Aircraft, A
Consistent
intent
Inconsistent
intent

10. HOW X(t) COMPONENTS ARE USED BY ATC
Based on preliminary field observations, controller seems to develop a ‘plan’ for their sector based on:
Current position of each aircraft
Future position based on velocity and heading
Future behavior based on knowledge/inference of intent (if available)
Monitors CONFORMANCE TO THE PLAN once established to determine if aircraft are adhering to presumed intent or whether any corrective action is required
Controller’s
target states
for a/c i
from IC(t)
CONFORMANCE
MONITORING
FUNCTION
Surveilled
states for
a/c i
Conforming to controller’s plan?

11. CONFORMANCE MONITORING
Controller compares surveillance data to internal representation of control system (pilot or autopilot), aircraft dynamics and measurement system performance
Hypothesis testing of whether aircraft is adhering to intended or cleared path:
State space hyper-tube
(may be probabilistic)
‘Off’ path
Target trajectory
‘On’ path
Previous waypoint
Next waypoint

12. FACTORS IMPACTING CONFORMANCE CAPABILITY
Several hours of ZME HOST computer system data analyzed
Important factors affecting conformance capability:
Aircraft navigation equipage level
FMS
INS
VOR/DME
None of the above
Flight mode
Autopilot
Heading
Manual
Speed
Altitude
Maneuver
Location wrt navaids
Pilot experience

13. TYPICAL FMS TRACKING BEHAVIOR (A320)
Cross-track deviation (nm)

14. TYPICAL VOR/DME TRACKING BEHAVIOR (B732)
Cross-track deviation (nm)

15. TYPICAL UNEQUIPPED TRACKING BEHAVIOR (Cessna 172)
Cross-track deviation (nm)

16. TRACKING VARIABILITY WITH A/C TYPE & EQUIPAGE
Jets (FMS)
Jets (DME)
Props (DME)
Average cross-track deviation (nm)
GA (DME)
GA (no DME)
+/- 1 SD from
average
• Raw data: ZME host computer, 5/26/99 (courtesy Mike Paglione, FAA Tech Center)
• Cross track deviations measured when established on track • Minimum of 5 hrs of data per type

17. AIRCRAFT TYPE ALTITUDE & SPEED COMPARISON
Typical cruise characteristics:
Higher altitude = larger error using angular navaids (VOR/DME)
Higher speed = larger deviation off path in a given amount of time for similar control systems

18. CONFORMANCE MONITORING AS HYPOTHESIS TESTING: ON OR OFF INTENDED PATH
FLIGHT PLAN
Aircraft capability (equipage, speed)
Flight phase (climb/descend/turn)
VOICE COMMS
Pilot capability
Flight mode (if requested)
RADAR
Location
(altitude, position
wrt navaids,
speed)
Internal model of plan & capability of aircraft i, ICi(t)
Measured
dynamic
states
Target states &
tolerances for a/c i
CONFORMANCE MONITORING
FUNCTION +
Commands / vectors to
re-establish
consistent intent
Lag -
Within tolerance?
Yes

19. CONCLUSIONS
Surveillance state vector combines traditional dynamic states of position, velocity & acceleration with higher order intent states
Intent states are essential for projecting dynamic states into future, enabling controller to formulate a plan for the behavior of the aircraft in the sector
Maintain safe separation
Manage flow efficiently
Current controller knowledge of intent is implicit & noisy
Conformance monitoring task establishes how well intent is being followed and whether controller intervention is required
Benefit of explicit intent to be investigated
Datalink
Procedures

20. BACKUP SLIDES

21. CONTROL THEORY ANALOGY
Noise
Aircraft & Pilot
Noise
XT(t) + + + + B  H + +
Surveillance
system A
e.g. vectors
Control inputs
Controller estimates B*
XS(t) + + +
Kalman
filter
Control
function  + - A*
Desired
states H*

22. PILOT / AIRCRAFT INTERACTION
PILOT i
Pilot’s
INTENT
IPi(t) i
Pilot’s
internal
target
states
CONTROL
LAW
Pilot manual
control OR -
FMS or
MCP
inputs
Aircraft i
trajectory
CONTROL
LAW
Autopilot
Aircraft
INTENT
IAi(t) ∫ ∫
A/c
target
states
Control
surface
inputs
Ai(t)
Vi(t)
Ri(t) -
Lag
AIRCRAFT i
Actual dynamic states

23. PILOT / CONTROLLER INTERACTION
Ground automation INTENT for
a/c i, IGi(t)
CONTROLLER
Controller’s ‘plan’
Traffic
Weather
Restrictions
PILOT i
Controller’s INTENT
for a/c i, ICi(t)
Pilot’s
INTENT
IPi(t)
Flight Plan
Voice comms j k
...
Controller’s
target
states
for a/c i
Lag
Vectors
Measured dynamic
states
A/c equipage
Pilot experience
Weather
Conformance
monitoring
for aircraft i
Surveillance
system j k
...

24. CONTROLLER / PILOT / AIRCRAFT INTERACTION LOOP
PILOT i
Measured dynamic states
Surveillance
system
Controller’s target
states for a/c i
Lag
CONTROLLER . :
Conformance
monitoring
for a/c i
Controller’s
INTENT
for a/c i, ICi(t) k
Pilot’s
INTENT
IPi(t)
Vectors j
Voice comms k
... j
Flight Plan
Flight Strip
Controller’s ‘plan’
FMS
inputs
CONTROL
LAW
Autopilot
A/c
INTENT
IAi(t) ∫ ∫
A/c
target
states
Control
surface
inputs i
Ai(t)
Vi(t)
Ri(t) -
Lag
Actual dynamic states
Trajectories
of aircraft
in sector
AIRCRAFT i

25. ! EXAMPLE USES OF INTENT Free flight FMS trajectory with
conformance bounds !
Downlink:
Present states: position, velocity, etc
Future states: e.g. 4D FMS trajectory,
heading mode, etc.
Uplink: modified clearances
direct to FMS

26. FUTURE WORK Implications for ADS-B content
Basis for new conflict detection algorithms
New paradigm for issuing control clearances
Analyze benefits of making more intent information available to the controller:
Could controller use/send other information from/to the aircraft to better understand/communicate intent
Downlink of autopilot flight mode?
Automated conformance monitoring systems
Datalink direct from/to FMS?